针对狭长空间无人车辆路径规划系统,提出一种基于改进的快速搜索随机树(rapidly-exploring random trees,RRT)路径规划算法,以解决传统RRT算法随机性较大、路径缺乏安全性的问题.该算法通过加入自适应目标概率采样策略、动态步长策略对...针对狭长空间无人车辆路径规划系统,提出一种基于改进的快速搜索随机树(rapidly-exploring random trees,RRT)路径规划算法,以解决传统RRT算法随机性较大、路径缺乏安全性的问题.该算法通过加入自适应目标概率采样策略、动态步长策略对传统的RRT算法进行改进,同时考虑到实际情况中无人驾驶车辆的动力学约束,该算法加入车辆碰撞约束和路径转角约束,并针对转角约束会导致迭代次数激增的问题提出了一种限制区域内随机转向的策略,最终得到一条安全性较高的路径.采用计算机仿真对所提算法和现有算法的性能进行对比验证.所提算法在狭长空间相较于传统人工势场引导下的RRT算法迭代次数降低了33.09%,规划时间减少了6.44%,路径长度减少了0.06%,并且在简单环境和复杂障碍物环境下规划能力均有提升.所提算法规划效率更高、迭代次数更少.展开更多
To improve the handling performance of a steer-by-wire (SBW) vehicle, a series of control logics are proposed. Firstly, an algorithm for enhancing the maneuvering in steady-state cornering is presented. On this basis,...To improve the handling performance of a steer-by-wire (SBW) vehicle, a series of control logics are proposed. Firstly, an algorithm for enhancing the maneuvering in steady-state cornering is presented. On this basis, two categories of control strategies are used to dynamically correct and compensate the transient state steering responses and vehicle behaviors. Simulator tests including subjective evaluations and virtual field tests are both conducted to make comprehensive investigations on the series of control logics. The subjective evaluations demonstrate that the SBW vehicle with a specifically selected value of steering sensitivity tends to be more desirable for driving than a conventional one in which a fixed steering ratio exists. The virtual field tests indicate that the control strategies for dynamical correction and compensation could effectively improve the handling per-formances of an SBW vehicle by reducing the work load of drivers, enhancing the track-holding performance, and improving steering response properties.展开更多
To improve maneuverability and stability of articulated vehicles, we design an active steering controller, including tractor and trailer controllers, based on linear quadratic regulator(LQR) theory. First, a three-deg...To improve maneuverability and stability of articulated vehicles, we design an active steering controller, including tractor and trailer controllers, based on linear quadratic regulator(LQR) theory. First, a three-degree-of-freedom(3-DOF) model of the tractor-trailer with steered trailer axles is built. The simulated annealing particle swarm optimization(SAPSO) algorithm is applied to identify the key parameters of the model under specified vehicle speed and steering wheel angle. Thus, the key parameters of the simplified model can be obtained according to the vehicle conditions using an online look-up table and interpolation. Simulation results show that vehicle parameter outputs of the simplified model and Truck Sim agree well, thus providing the ideal reference yaw rate for the controller. Then the active steering controller of the tractor and trailer based on LQR is designed to follow the desired yaw rate and minimize their side-slip angle of the center of gravity(CG) at the same time. Finally, simulation tests at both low speed and high speed are conducted based on the Truck Sim-Simulink program. The results show significant effects on the active steering controller on improving maneuverability at low speed and lateral stability at high speed for the articulated vehicle. The control strategy is applicable for steering not only along gentle curves but also along sharp curves.展开更多
文摘针对狭长空间无人车辆路径规划系统,提出一种基于改进的快速搜索随机树(rapidly-exploring random trees,RRT)路径规划算法,以解决传统RRT算法随机性较大、路径缺乏安全性的问题.该算法通过加入自适应目标概率采样策略、动态步长策略对传统的RRT算法进行改进,同时考虑到实际情况中无人驾驶车辆的动力学约束,该算法加入车辆碰撞约束和路径转角约束,并针对转角约束会导致迭代次数激增的问题提出了一种限制区域内随机转向的策略,最终得到一条安全性较高的路径.采用计算机仿真对所提算法和现有算法的性能进行对比验证.所提算法在狭长空间相较于传统人工势场引导下的RRT算法迭代次数降低了33.09%,规划时间减少了6.44%,路径长度减少了0.06%,并且在简单环境和复杂障碍物环境下规划能力均有提升.所提算法规划效率更高、迭代次数更少.
基金Project (Nos. 50475009 and 50775096) supported by the National Natural Science Foundation of China
文摘To improve the handling performance of a steer-by-wire (SBW) vehicle, a series of control logics are proposed. Firstly, an algorithm for enhancing the maneuvering in steady-state cornering is presented. On this basis, two categories of control strategies are used to dynamically correct and compensate the transient state steering responses and vehicle behaviors. Simulator tests including subjective evaluations and virtual field tests are both conducted to make comprehensive investigations on the series of control logics. The subjective evaluations demonstrate that the SBW vehicle with a specifically selected value of steering sensitivity tends to be more desirable for driving than a conventional one in which a fixed steering ratio exists. The virtual field tests indicate that the control strategies for dynamical correction and compensation could effectively improve the handling per-formances of an SBW vehicle by reducing the work load of drivers, enhancing the track-holding performance, and improving steering response properties.
基金supported by the Program for Changjiang ScholarsInnovative Research Team in University,China(No.IRT0626)
文摘To improve maneuverability and stability of articulated vehicles, we design an active steering controller, including tractor and trailer controllers, based on linear quadratic regulator(LQR) theory. First, a three-degree-of-freedom(3-DOF) model of the tractor-trailer with steered trailer axles is built. The simulated annealing particle swarm optimization(SAPSO) algorithm is applied to identify the key parameters of the model under specified vehicle speed and steering wheel angle. Thus, the key parameters of the simplified model can be obtained according to the vehicle conditions using an online look-up table and interpolation. Simulation results show that vehicle parameter outputs of the simplified model and Truck Sim agree well, thus providing the ideal reference yaw rate for the controller. Then the active steering controller of the tractor and trailer based on LQR is designed to follow the desired yaw rate and minimize their side-slip angle of the center of gravity(CG) at the same time. Finally, simulation tests at both low speed and high speed are conducted based on the Truck Sim-Simulink program. The results show significant effects on the active steering controller on improving maneuverability at low speed and lateral stability at high speed for the articulated vehicle. The control strategy is applicable for steering not only along gentle curves but also along sharp curves.
